Integration will extend platform to data scientists and full-code developers & help them bring AI & ML applications to market faster
By Steve Bauer, Infor Vice President, Public Relations
Infor is announcing the integration of Jupyter Notebook with its Infor Coleman Artificial Intelligence (AI) and Machine Learning (ML) platform, which will extend the citizen developer platform to data scientists and full-code machine learning developers and enable them to bring AI & ML applications to market faster.
Jupyter Notebook is a web-based interactive computing platform, designed to support interactive data science and scientific computing across multiple programming languages. It is considered one of the industry’s leading interactive development environments (IDEs) for notebooks, code and data.
The integration with Infor Coleman enables datasets to be used in Jupyter Notebook in an easy and familiar way. Data scientists and developers can use the platform with built-in Python libraries and features such as an intelligent editor to explore data, develop algorithms, and test them efficiently to expedite AI/ML deployments and deliver value faster.
“The convenience of the Jupyter Notebook experience, combined with the power of Infor’s Coleman AI and Machine Learning Platform, can enable faster and more successful AI and ML projects,” said Brad Stillwell, Infor VP of product management. “Users can develop their scripts in a single platform, without the need for a separate interactive development environment. And the integration provides a way for them to explore, manipulate, clean and develop their data, as part of the typical data science workflow, making it immediately available for production.”
With the Jupyter Notebook experience and Infor Coleman, users can more quickly develop AI/ML applications and bring them directly into production environments. These could include asset performance management applications designed to improve safety and increase efficiency in manufacturing environments, for example, or applications that incorporate sensor data from the factory floor, enabling better predictive maintenance and quality-control strategies.
Further, developers using Jupyter Notebook in combination with Infor Coleman could create AI/ML applications that provide distributors with the visibility they need to mitigate supply chain disruptions before they occur. And they could develop applications that help distributors improve customer service and retention.
Likewise, applications developed with the platform could help companies in service industries get better visibility into inventory and labor needs, so they can improve operations.
‘Jupyter Notebooks in Infor Coleman AI’ video to learn more about how the Jupyter Notebook integration with the Infor Coleman AI/ML platform will help developers rapidly build and deploy custom algorithms to solve applied AI/ML use cases.
Additional capabilities and features enabled by integrating Jupyter Notebook with the Infor Coleman AI/ML platform include:
- Prebuilt big data integration with Infor’s data fabric
- The modular nature of the notebook enables easy testing and debugging of small segments of code.
- With the coding playground, users can try out, prepare and test their code in the Infor Coleman AI/ML platform before packaging and deploying their custom algorithm to production.
- Developers can turn their custom algorithms into deployed models with automatically generated API endpoints. These can be consumed across Infor’s platform technology, including embedding them into Infor’s ERP systems with in-context widgets.
- Schedule periodic retraining using an Infor ION workflow or pass the data back to the data lake so results are available to widgets, dashboards and Infor Birst analytics.
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